Automated SEM/EDS Analysis and Classification of Forensic Samples

New generation SEMs incorporate computer automation and detector technology that allows for rapid elemental analyses of small particles. Already the gold standard for GSR analysis, the technique is being evaluated for forensic soil comparisons.

Speed, accuracy, and consistency are keys for moving forensic caseloads from the lab to the courtroom. Crime laboratories have long employed scanning electron microscopes (SEM) for use in trace element cases, including analysis of glass, paint, fibers, and gunshot residue (GSR). The newest generation of SEM, utilizing energy dispersive x-ray spectrometers (EDS), incorporates computer automation that allows for rapid automated elemental analyses of small particles or inclusions (Figure 1). These automated analyses yield chemical and morphological information which can be used to characterize specific populations of materials present in a forensic sample.This technique removes operator subjectivity inherent in time intensive manual SEM or optical characterization techniques, and allows rapid characterization of all the materials present in a sample. Currently the gold standard for gunshot residue analysis, the usefulness of automated SEM-EDS is being evaluated for other trace evidence cases, specifically forensic soil comparison.

By performing an automated SEM-EDS analysis,more particles can be analyzed per unit time, allowing for efficient and more complete sample characterization. For example, specialized SEM-EDS systems, utilizing new software algorithms, can now analyze and classify between 500-1,500 particles per hour, and current trends in detector technology promise to further improve this rate. Automated SEM-EDS also increases the probability of finding and identifying rare materials that are characteristic of forensic and environmental samples. For these reasons, automated SEM-EDS analysis is becoming a fundamental tool used by crime labs.

Automated SEM Analysis
Whereas a light microscope uses visible light and lenses to magnify a sample for analysis, an elemental analysis in an SEM, whether manual or automated, involves the interaction of a high-energy electron beam with the sample of interest, resulting in the generation of back scattered electrons (for imaging), and characteristic x-rays (for elemental analysis). Back scattered electrons are high-energy electrons that are elastically scattered from within the specimen. Higher atomic number (Z) elements tend to back scatter more electrons, and therefore appear brighter (higher gray-level value) than lower Z materials in back scattered electron images (BEI) (Figure 2).

During an automated elemental analysis, these contrast differences can be used to set thresholds to highlight the particles or compositions of interest,while ignoring ubiquitous materials. For example, during a GSR analysis,minerals or organic particles may not be of interest. These particles are primarily composed of lower atomic number elements and therefore yield darker BEI images than GSR particles,which are composed of higher Z elements: lead, barium, and antimony. The gray-level thresholding utilized in the automated software can be used to highlight brighter particles and skip ubiquitous darker materials (Figure 2). Note the software is easily capable of discerning particles with very similar grayscale values. The software can also use morphological parameters to locate particles of interest such as fibers and elongated minerals.

Sample Preparation
Sample preparation is of fundamental importance to achieve the best analytical results. Techniques will vary depending on the type of material being analyzed, and the focus of the study. Properly prepared samples must fit in the sample chamber, be vacuum compatible, and must not become electrically charged during the analysis.

GSR samples are typically prepared on carbon sticky tabs which have been placed on an aluminum mount and patted on the questioned article.The sample may need to be coated to prevent the build-up of electric charge on the sample surface if analyzed under high vacuum. Many new SEM systems are equipped to operate in variable pressure or low vacuum mode,where the sample is at a higher pressure than the electron column, reducing charge build-up. These types of instruments allow a wider variety of materials to be analyzed and may reduce the need to coat non-conductive samples. This is important for forensic samples, specifically GSR analysis, because the sample can be preserved in original condition in case further analyses need to be performed.

Sample preparation for the forensic comparison of soils can be more complicated. Due to the amount of material, special techniques must be employed to limit the amount of contact between particles. Particles that touch or overlap one another are identified as a single particle by the SEM software, often leading to an incorrect or inconclusive material identification. A reverse sieving technique first described by McVicar and Graves from the Centre of Forensic Sciences in Toronto, Canada, has proven to be effective in reducing the number of touching and overlapping particles.2 In this technique, representative sub-samples of soils are sieved, separated into target size fractions, and reverse sieved onto sticky carbon tabs.As the stack of sieves is shaken, a fraction of the sample gets left on the screen in each representative size fraction.The particles in these sub-samples have a range of diameters from the sizes of the larger sieve mesh directly above it to the smaller mesh it sits on. For reverse sieving, the mesh size difference between the pairs of adjoining sieves in the sieve stack should be as small as possible allowing only one grain to fall back through each opening in the sieve, creating a grid like pattern of particles (Figure 3). If more than one grain falls to the adhesive stub through a single screen opening, the two particles can touch and therefore confound results of the subsequent automated SEM-EDS analysis.Due to differences in a mineral’s chemical and mechanical weathering rates,multiple size fractions should be analyzed to accurately classify the soil.

Applications for Forensics (Gunshot Residue)
The forensic community has long used automated SEM-EDS analysis for performing gunshot residue (GSR) testing. A GSR analysis is similar to contaminant analyses performed in other industries in that it involves analysis of a dispersion of particles for specific materials of interest. For GSR analysis, a carbon sticky tab which has been placed on an aluminum mount is patted on the article in question and subsequently analyzed for particles containing lead, barium, and antimony (or combinations of the three elements). These elements are primary components of the primer used to ignite the propellant in ammunition.3 In addition to the chemical information, the morphology of the particles is also of interest, as these particles should be rounded, fused, spherical, and/or non crystalline due to exposure to high temperatures during the discharge of the firearm and subsequent rapid cooling.1,3 With an automated SEM-EDS analysis, both elemental and morphological properties of GSR particles can be determined in a rapid and accurate manner; ancillary materials which may be of interest in a forensic investigation can also be characterized.

Applications for Forensics (Forensic Soil Identification)
The forensic comparison of soils may involve use of many different techniques to prove or disprove possible similarities between known, questioned, or alibi samples. The common approach has been to use soil color, particle size distribution (relative portions of gravel, sand, silt, and clay), texture, and biological or anthropogenic materials to determine similarities and differences between the soils in question.4,5 Unlike a GSR analysis where specific materials of interest are the main focus, the purpose of forensic soil analysis using automated SEM-EDS analysis is to classify all of the particulate material on the stub. Given time and costs, this is often not possible using manual techniques.

If a lab is fortunate enough to have a skilled optical mineralogist on staff, the identification of individual mineral grains may also prove valuable when comparing soils. Traditionally, polarized light microscopy (PLM) has been the technique used to classify the mineral constituents in soils,whether for forensic purposes or not. This involves having a trained optical mineralogist manually search the sample and tally the number of each mineral type identified. There are several limitations that are associated with this technique.Most notably is the need for crime labs to have the services of a skilled optical mineralogist. This method is also very time consuming, statistics are relatively poor because of the low number of particles that can be classified in a reasonable time frame, and the results are based on the mineralogist’s subjective observations, lending to possible confirmatory biases.2 Due to the small number of particles characterized, rare mineral phases which may be characteristic of particular soils are more difficult to find.

It is expected that many of the limitations of manual, optical classifications of soil will be overcome by performing automated elemental analyses of soil preparations using SEM-EDS. These analyses should provide more statistically reliable and reproducible data, due to the larger sample size, as well as better ability to find rare mineral phases or “needle in a haystack” particles.2,6,7 In addition,many anthropogenic materials, such as steels and other metals, identified during this automated analysis may provide additional forensic evidence. This technique is still being cultivated and techniques are being refined through the analysis of mineral standards, the development of rule files for chemical classification of particles, and the analysis and comparison of soil standards. However, the usefulness of automated SEM-EDS soil analysis is empirically apparent, and ongoing research is needed to determine the accuracy and reproducibility of this technique.

Applications for Forensics (Environmental Samples)
Automated elemental analyses can also be utilized for the general classification of materials in environmental samples.The Environmental Protection Agency, along with other environmental and health organizations, has recently focused on airborne particulates and their adverse health effects on the population. For reasons mentioned above, an automated SEM system is ideal for analyzing and classifying unknown materials on filters collected from air filtration monitoring systems. These collections may occur downwind from an industrial complex suspected of releasing harmful foreign materials into the air. Filters can also be placed in scrubbers to monitor the amount and type of particulate being released into the air from manufacturing facilities. The same general principles can be applied to the analysis of filtered particulate from waste effluent or other water samples.

Conclusions
New generation SEMs, utilizing energy dispersive x-ray spectrometers, incorporate computer automation and detector technology that allow for rapid elemental analyses of small particles or inclusions. Automated SEM-EDS analyses remove biases inherently present in manual optical or SEM analyses and provide elemental and morphological information.This technique allows for a more complete characterization of particulate within a sample in a time-efficient manner. Whether the analysis involves searching a sample for specific materials of interest, or classification of all particulate within a sample, automated SEM-EDS can provide rapid and accurate results. It is currently the gold standard for gunshot residue analysis, and its utility is presently being evaluated for other trace evidence areas, specifically forensic soil comparison.